The goals of this review paper on deep learning (DL) in medical imaging and radiation
therapy are to (a) summarize what has been achieved to date;(b) identify common and …

Highlights•Deep learning technology has gained remarkable success.•We highlight the
recent applications of deep learning in drug discovery research.•Some popular deep …

In this paper, we first describe the basics of the field of cancer diagnosis, which includes
steps of cancer diagnosis followed by the typical classification methods used by doctors …

Deep learning has rapidly advanced in various fields within the past few years and has
recently gained particular attention in the radiology community. This article provides an …

In this review the application of deep learning for medical diagnosis is addressed. A
thorough analysis of various scientific articles in the domain of deep neural networks …

The use of machine learning (ML) has been increasing rapidly in the medical imaging field,
including computer-aided diagnosis (CAD), radiomics, and medical image analysis …

Given the potential risk of X-ray radiation to the patient, low-dose CT has attracted a
considerable interest in the medical imaging field. Currently, the main stream low-dose CT …

In this paper, we aim to provide a survey on the applications of deep learning for cancer
detection and diagnosis and hope to provide an overview of the progress in this field. In the …

Deep learning (DL) algorithms have rapidly become a robust tool for analyzing medical
images. They have been used extensively for medical image segmentation as the first and …

Convolutional Neural Networks (CNNs) have been recently employed to solve problems
from both the computer vision and medical image analysis fields. Despite their popularity …